For interfaces complying with ORI (Open Radio equipment Interface) which is an international standard, data compression techniques have been studied for the purpose of reducing the transfer rate of the IQ signal between the REC (Radio Equipment Control) and the RE (Radio Equipment) (see, for example, Non-PTLS 1 to 3).
Data compression techniques of the IQ signal include down-sampling (reduction of sampling rate), and non-linear quantization (reduction of transmission bit number).
By utilizing the characteristics in which the distribution of the signal amplitude of the real part and the imaginary part (hereinafter referred to as IQ) is a regular distribution (see, for example, FIG. 1(a)), the non-linear quantization employs an algorithm for reducing the transmission bit number of each sample by use of the cumulative distribution function (CDF) of the amplitude of the IQ signal (see, for example, FIG. 1(b)). To be more specific, in non-linear quantization, the quantization threshold is set such that the sample value corresponding to the amplitude having a higher occurrence probability is more correctly indicated (the quantization error is reduced) in comparison with the sample value corresponding to the amplitude having a lower occurrence probability in consideration of the frequency of generation (occurrence probability) of the amplitude of the input signal. That is, in the amplitude distribution of the IQ signal, the interval of the quantization threshold of the amplitude having a high occurrence probability (the amplitudes around the average value) is set to a value smaller than the interval of the quantization threshold of the amplitude having a low occurrence probability (see, for example, FIG. 1(c)).
Cumulative distribution function g(x) of the regular distribution can be expressed with error function (erf) as in Expression (1).
                    [                  Expression          ⁢                                          ⁢          1                ]                                                                      g          ⁡                      (            x            )                          =                              1            2                    ⁢                      (                          1              +                              erf                ⁡                                  (                                      x                                                                  2                        ⁢                                                                                                  ⁢                        σ                                                                              )                                                      )                                              (        1        )            
In Expression (1), x is an integer value representing the IQ signal for compression (that is, the input signal), which falls within the range of [−2N−1, . . . , 2N−1−1] (N is a natural number). For example, a sample value of input signal x is represented by N=15 bits, for example. In addition, σ represents a standard deviation.
Next, the value of function g(x) expressed by Expression (1) is associated with sample value h(x) (that is, quantization data) of the IQ signal after compression in accordance with Expression (2).[Expression 2]h(x)=|g(x)*(2M−1)|  (2)
In Expression (2), h(x) is an integer value representing quantization data, which falls within the range of [0, . . . , 2M−1] (M is a natural number smaller than N). The sample value of the quantization data is represented by M=10 bits, for example. In addition, the right side of Expression (2) is a minimum integer of g(x)*(2M−1) or greater.
That is, in the above-mentioned example, the input signal of N=15 bits is compressed into quantization data of M=10 bits by non-linear quantization.